ASSESSING THE IMPACT OF COMPUTER AIDED-DRAWING TOOLS ON CREATIVITY DURING THE CONCEPTUAL STAGE OF THE ARCHITECTURAL DESIGN PROCESS: A PROOF-OF-CONCEPT STUDY

Authors

DOI:

https://doi.org/10.18623/rvd.v22.n4.3761

Keywords:

Architectural Design Process, CAD Tools, Conceptual Design Stage, Creativity, Protocol Analysis

Abstract

This empirical study is a proof-of-concept that investigates the influence of computer-aided drawing (CAD) tools on creativity during the conceptual stage of architectural design. The used protocol analysis method enables an in-depth examination of the design process through both graphical outputs and cognitive processes. The study uses defined coding schemes and metrics to assess specific creativity indicators derived from protocol analysis quantitatively. Four third-year architecture students were assigned two design tasks: the first involved traditional freehand sketching and the second employed CAD tools. A comparative analysis of the two sets of protocols indicates that an early reliance on CAD tools tends to result in a less creative, more repetitive and mechanical design process. This is in contrast to designs produced exclusively through freehand sketching. Furthermore, a qualitative assessment of the resulting designs by a jury, shows that hand-drawn designs were more creative and original than those produced by CAD-assisted processes. These results suggest that architecture educators should prioritise hand drawing in the initial stages of the design process, introducing digital tools at a later stage, once creative ideas have been developed. This ensures a balanced curriculum that values both approaches. In practice, architects should use CAD strategically after producing an initial hand-drawn sketch to maintain creative and innovative design processes rather than relying too heavily on CAD. These findings emphasise the importance of integrating both methodologies to enhance architectural education and professional practice.

References

Allport, G.W. (1954). The Nature of Prejudice, Addison-Wesley, Cambridge, MA, USA.

Ametordzi, S., & Olalere F.E. (2024). The effect of digital technology on graphic design ideation output, IDA: International Design and Art Journal 6(1): 144-156.

Anderson, J.R., & Simon, H.A. (1999). Learning by doing: An exploration of mental models, Cognitive Science 23(4): 571-602, https://doi.org/10.1207/s15516709cog2304_3

Antoniades, A.C. (1990). Poetics of Architecture: Theory of Design, Van Nostrand Reinhold, New York, USA.

Arrouf, A. (2012). Towards a scientific theory of architectural design. Contribution to architectural epistemology and to the modeling of the act of designing [Vers une théorie scientifique de la conception architecturale. Contribution à l’épistémologie architecturale et à la modélisation de l’acte de concevoir], European University Publishing, Saarinen, Germany.

Arrouf, A., & Bensaci, A. (2006). Modeling of the design process, experimental study of the compositional system, design instance [Modélisation du processus de conception, étude expérimentale du système compositionnel, instance conception], in: Courrier du savoir, University of Biskra 7(7): 67-86.

Atef, M., & Wahba, K. (2023). The impact of using computer-aided design (CAD) on the creativity of architecture students, Journal for Educators, Teachers and Trainers 14(4): 245-256, https://doi.org/10.47750/jett.2023.14.04.021

Bajúzová, M., & Hrmo, R. (2024). Digital tools in education: The impact of digital tools in education on students’ creativity, R&E-SOURCE 1(s1): 4-18, https://doi.org/10.53349/resource.2024.is1.a1236

Broadbent, D.E. (1983). Focused and divided attention to dichotic wordstreams, Acta Psychologica 53(1): 1-16.

Casakin, H., & Goldschmidt, G. (2000). Reasoning by visual analogy in design problem-solving: the role of guidance, Journal of Planning and Design in Environment & Planning B 27: 105-119, https://doi.org/10.1068/b2565

Chan, C.S. (1995). A cognitive theory of style, Environment and Planning B: Planning and Design 22(4): 461-474.

Chen, Q. et al. (2025). Dynamic switching between brain networks predicts creative ability, Communications Biology, 8(1): 54, https://doi.org/10.1038/s42003-025-07470-9

Cina, M., & Paraponaris, C. (2022). Hindered Creativity? Creative Support Techniques through the Organological Approach [Une créativité entravée ? Les techniques d’aide à la création selon l’approche organologique], Gestiòn Internacional 26(2): 31-46, https://doi.org/10.7202/1089020ar

Craig, D.L. (2001). Comparison of research strategies for studying design behaviour, design knowing and learning, Psychological Review, 13-36, https://doi.org/10.1016/B978-008043868-9/50002-4

Cross, N., Christiaans, H., & Dorst, K. (1996). Analysing Design Activity, John Wiley & Sons Ltd., Chichester, UK.

Dorst, K., & Cross, N. (2001). Creativity in the design process: co-evolution of problem–solution, Design Studies 22(5): 425-437.

Finke, R.A. (1990). Creative Imagery: Discoveries and Inventions in Visualization, Lawrence Erlbaum Associates, Hillsdale, NJ, USA.

Frich, J., Nouwens, M., Halskov, K., & Dalsgaard, P. (2021). How digital tools impact convergent and divergent thinking in design ideation, in: CHI Conference on Human Factors in Computing Systems (CHI ’21), 8–13 May 2021, Yokohama, Japan, 431. https://doi.org/10.1145/3411764.3445062

Gero, J.S. (1999). Constructive memory in design thinking, in: Goldschmidt G., Porter W. (Eds.), Design Thinking Symposium: Design Representation, MIT, Cambridge, MA, USA, pp. I.29–35.

Gero, J.S., & McNeill, T. (1998). An approach to the analysis of design protocols, Design Studies 19(1): 21-61.

Gero, J.S., & Milovanovic, J. (2020). A framework for studying design thinking through measuring designers’ minds, bodies and brains, Design Science 6, https://doi.org/10.1017/dsj.2020.15

Goldschmidt, G. (1991). The dialectics of sketching, Creativity Research Journal 4: 123-143, https://doi.org/10.1080/10400419109534381

Goldschmidt, G. (1997). Capturing indeterminism: representation in the design problem space, Design Studies 18(4): 441-455.

Goldschmidt, G. (2005). Designing as a cognitive activity: the linkography method, in: Eastman C., Newstetter W., McCracken M. (Eds.), Designing Design Education, Georgia Institute of Technology, Atlanta, GA, USA, pp. 53-72.

Goldschmidt, G. (2010). Linkography: Unfolding the design process, MIT Press, Cambridge, MA, USA.

Goldschmidt, G., & Smolkov, M. (2006). Variances in the impact of visual stimuli on design problem solving performance, Design Studies 27: 549-569, https://doi.org/10.1016/j.destud.2006.01.002

Howard, T. J., Culley, S. J., & Dekoninck, E. A. (2009). Stimulating creativity: a more practical alternative to TRIZ, in: Proceedings of the 17th International Conference on Engineering Design (ICED'09), Stanford, CA, USA.

Hudson, L. (1966). Contrary Imaginations: A psychological study of the English schoolboy, Methuen, London, UK.

Kroll, E. (2013). Design theory and conceptual design: contrasting functional decomposition and morphology with parameter analysis, Research in Engineering Design 24(2): 165-183, https://doi.org/10.1007/s00163-012-0134-9

Lawson, B.R. (2002). CAD and creativity: does the computer really help?, Leonardo 35(3): 327-331, https://doi.org/10.1162/002409402760105361

MacKinnon, D.W. (1962). The personality correlates of creativity, in: Vernon P. E. (Ed.), Creativity, Penguin Books, Harmondsworth, UK, pp. 289-311.

Mille, C. (2021). Can digital tools impact innovation and creativity? [Les outils numériques peuvent-ils impacter l’innovation et la créativité ?], Doctoral Dissertation, Institut Arts et Métiers de Lava, France.

Newell, A. (1966). On the analysis of human problem-solving protocols, Carnegie-Mellon University, Pittsburgh, PA, USA.

Perttula, M. (2007). Designers’ use of sketches in idea generation, in: Proceedings of the 16th International Conference on Engineering Design (ICED 07), 24-27 July 2007, Paris, France, pp. 439–440.

Saliminamin, S., Becattini, N., & Cascini, G. (2019). Sources of creativity stimulation for designing the next generation of technical systems: correlations with R&D designers’ performance, Research in Engineering Design 30: 133-153, https://doi.org/10.1007/s00163-018-0299-2

Shai, O., Reich, Y., & Rubin, D. (2009). Creative conceptual design: extending the scope by infused design, Computer-Aided Design 41(3): 117-135, https://doi.org/10.1016/j.cad.2007.11.004

Sio, U.N., & Ormerod, T.C. (2009). Does incubation enhance problem solving? A meta-analytic review, Psychological Bulletin 135(1): 94-120, https://doi.org/10.1037/a0014212

Smith, M.B. (1964). Personality dynamics and the process of perceiving, in: Smith M B (Ed.), Personality Theory and Perception, Random House, New York, USA, pp. 1-23.

Suwa, M., Gero, J., & Purcell, T. (1998). Macroscopic analysis of design processes based on a scheme for coding designer’s cognitive actions, Design Studies 19: 455-483, https://doi.org/10.1016/s0142-694x(98)00016-7

Suwa, M., Gero, J.S, & Purcell, T. (1999). Unexpected discoveries: how designers discover hidden features in sketches, in: Gero J. S., Tversky B. (Eds.), Visual and Spatial Reasoning in Design, University of Sydney, Key Centre of Design Computing and Cognition, pp. 145-162.

Suwa, M., Gero, J.S., & Purcell, T. (2002). Unexpected discoveries and S-inventions of design requirements: important vehicles for a design process, Design Studies 23(5): 385-409, https://doi.org/10.1016/S0142-694X(02)00007-9

Suwa, M., & Tversky, B. (1996). What architects see in their sketches: implications for design tools, in: Human Factors in Computing Systems: CHI '96 Conference Companion, ACM, New York, pp. 191-192.

Suwa, M., & Tversky, B. (1997). What do architects and students perceive in their design sketches? A protocol analysis, Design Studies 18(4): 385-403, https://doi.org/10.1016/s0142-694x(97)00008-2

Suwa, M., Tversky, B., Gero, J.S., & Purcell, A.T. (2001). Analysis of sketches produced by architects and engineering students in an early design stage, Design Studies 22(5): 437-456, https://doi.org/10.1016/S0142-694X(01)00019-9

Tang, C., Mao, S., Naumann, S.E., & Xing, Z. (2022). Improving student creativity through digital technology products: a literature review, Thinking Skills and Creativity, Elsevier, https://doi.org/10.1016/j.tsc.2022.101032

Tang, H., Owen, C.L., & Khan, A.I. (2002). Design team performance in product concept generation: an experimental study, Design Studies 23(5): 495-515.

Viswanathan, V., & Linsey, J.S. (2018). Spanning the complexity chasm: a research approach to move from simple to complex engineering systems, Artificial Intelligence for Engineering Design, Analysis and Manufacturing 32(4): 470-482.

Xu, C., & Huang, Y. (2024). Technological innovation in architectural design education: empirical analysis and future directions of Midjourney intelligent drawing software, Buildings 14: 3288, https://doi.org/10.3390/buildings14103288

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Published

2025-11-25

How to Cite

Mohammedi, K., & Arrouf, A. (2025). ASSESSING THE IMPACT OF COMPUTER AIDED-DRAWING TOOLS ON CREATIVITY DURING THE CONCEPTUAL STAGE OF THE ARCHITECTURAL DESIGN PROCESS: A PROOF-OF-CONCEPT STUDY. Veredas Do Direito, 22, e223761. https://doi.org/10.18623/rvd.v22.n4.3761